Characteristics of hospitalised COVID-19 patients during the first two pandemic waves, Gauteng.

IF 1.4 Q4 INFECTIOUS DISEASES
Southern African Journal of Infectious Diseases Pub Date : 2022-09-30 eCollection Date: 2022-01-01 DOI:10.4102/sajid.v37i1.434
Mpho L Sikhosana, Waasila Jassat, Zinhle Makatini
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引用次数: 1

Abstract

Background: Gauteng province (GP) was one of the most affected provinces in the country during the first two pandemic waves in South Africa. We aimed to describe the characteristics of coronavirus disease 2019 (COVID-19) patients admitted in one of the largest quaternary hospitals in GP during the first two waves.

Objectives: Study objectives were to determine factors associated with hospital admission during the second wave and to describe factors associated with in-hospital COVID-19 mortality.

Method: Data from a national hospital-based surveillance system of COVID-19 hospitalisations were used. Multivariable logistic regression models were conducted to compare patients hospitalised during wave 1 and wave 2, and to determine factors associated with in-hospital mortality.

Results: The case fatality ratio was the highest (39.95%) during wave 2. Factors associated with hospitalisation included age groups 40-59 years (adjusted odds ratio [aOR]: 2.14, 95% confidence interval [CI]: 1.08-4.27), 60-79 years (aOR: 2.49, 95% CI: 1.23-5.02) and ≥ 80 years (aOR: 3.39, 95% CI: 1.35-8.49). Factors associated with in-hospital mortality included age groups 60-79 years (aOR: 2.55, 95% CI: 1.11-5.84) and ≥ 80 years (aOR: 5.66, 95% CI: 2.12-15.08); male sex (aOR: 1.56, 95% CI: 1.22-1.99); presence of an underlying comorbidity (aOR: 1.76, 95% CI: 1.37-2.26), as well as being admitted during post-wave 2 (aOR: 2.42, 95% CI: 1.33-4.42).

Conclusion: Compared to the recent omicron-driven pandemic waves characterised by lower admission rates and less disease severity among younger patients, COVID-19 in-hospital mortality during the earlier waves was associated with older age, being male and having an underlying comorbidity.

Contribution: This study showed how an active surveillance system can contribute towards identifying changes in disease trends.

豪登省前两波大流行期间住院COVID-19患者的特征
背景:在南非前两波大流行期间,豪登省是该国受影响最严重的省份之一。我们的目的是描述前两波在GP最大的第四医院之一入院的2019冠状病毒病(COVID-19)患者的特征。目的:研究目的是确定与第二波住院相关的因素,并描述与院内COVID-19死亡率相关的因素。方法:采用全国医院COVID-19住院监测系统的数据。采用多变量logistic回归模型比较第1波和第2波住院患者,并确定与住院死亡率相关的因素。结果:第二波病死率最高,为39.95%。与住院相关的因素包括40-59岁年龄组(调整优势比[aOR]: 2.14, 95%可信区间[CI]: 1.08-4.27)、60-79岁年龄组(aOR: 2.49, 95% CI: 1.23-5.02)和≥80岁年龄组(aOR: 3.39, 95% CI: 1.35-8.49)。与住院死亡率相关的因素包括60-79岁年龄组(aOR: 2.55, 95% CI: 1.11-5.84)和≥80岁年龄组(aOR: 5.66, 95% CI: 2.12-15.08);男性(aOR: 1.56, 95% CI: 1.22-1.99);存在潜在的合并症(aOR: 1.76, 95% CI: 1.37-2.26),以及在术后第2波住院(aOR: 2.42, 95% CI: 1.33-4.42)。结论:与最近由组粒驱动的大流行波相比,年轻患者的入院率较低,疾病严重程度较低,早期波期间的COVID-19住院死亡率与年龄较大、男性和潜在合并症有关。贡献:本研究显示了主动监测系统如何有助于确定疾病趋势的变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
自引率
11.10%
发文量
50
审稿时长
52 weeks
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